As it is known by the person skilled in the art, the optical imaging of biological samples can be achieved through a large number of methods that can be classified, for the sake of simplicity, in three classes according to the physical mechanisms by which optical contrast is obtained.
The first class refers to methods based on spatial variations of the light transport properties. The classical methods are mainly based on contrast of absorption, reflectivity, refringence, birefringence, or polarization. Whatever the light transport property, it does not yield direct information about the sample biochemistry.
The second class refers to methods based on contrasts produced by “extrinsic” signals resulting from the optical excitation of well defined extrinsic luminescent molecules, introduced in the sample and selected both for giving strong optical signals and specific molecular recognition properties. The use of extrinsic luminescent contrast agents is time-consuming and requires constraining labelling procedures.
The third class refers to methods based on contrasts produced by “intrinsic” signals resulting from the optical excitation of well defined intrinsic molecules naturally present in the sample. Classically these methods offer lateral and depth resolutions which are insufficient for revealing the intimate tissue structures at cellular and subcellular scales.
The methods of the second and third classes may be based on the linear or non-linear optical response. But, as explained hereafter, it is preferable to use the non-linear optical response.
Indeed, when imaging intrinsic or extrinsic signals deep into a sample that is thicker than the depth of focus, the light must be directed toward the focus plane, and contrast information must be directed backwards or forward to the detector. So, an optimal light transport would require that the sample be transparent for excitation and emission light, and an optimal contrast would require that the sample not be transparent to the molecular excitations.
It results from this paradox that i) linear imaging microscopy technique can hardly perform deep tissue imaging and ii) endoscopic fluorescence imaging cannot resolve signals coming from the surface from those produced by deep chromophores. In contrast, the non-linear imaging uses a long wavelength near-infrared laser light which is in the transparency spectral window of the biological sample. So, the excitation light minimally interacts with the tissue on its way to the focus, which means that the transparency/excitation paradox of linear imaging techniques is solved, at least within a useful light penetration boundary which is currently at around 0.5 mm with excitation wavelength in the 700-1100 nm range. But, as in the case of linear fluorescence microscopy, intrinsic signals are considered as background noise and filtered out with appropriate optical filters.
Methods have also been proposed for extracting information about the metabolic status of a biological sample, in vivo or ex vivo, or for resolving histopathological features, like the malignancies of tumors, using intrinsic fluorescence or Raman emission spectra and lifetime. But, these so-called “spectral pathology” methods have been implemented with a linear excitation, thus leading to three major disadvantages:                i) since excitation is not confined at a focus, the linear spectroscopy is not spatially resolved and intrinsically bears strong limitations in terms of lateral and depth resolutions, as well as deep imaging.        ii) “Single-photon” fluorescence excitation spectra most often display a single and narrow peak, and one laser wavelength will only excite few molecular components. This puts stringent conditions on the choice of excitation wavelengths, and often leads to complicated spectroscopic criteria for resolving pathologic situations from healthy ones. This is for instance the case of intrinsic imaging of skin lesions or single point intrinsic fluorescence spectroscopy of the colon, where several wavelengths are necessary for one discrimination.        iii) Since spectral anomalies are produced by molecular sources which are not uniformly distributed in the sample, but most likely concentrated in specific cell types or subcellular structures, their spectroscopic contribution might be locally dominant in the wavelength and lifetime domain. Nevertheless, these local contributions are never dominant features in the final spectrum and therefore are difficult to extract, because they are spatially averaged out.        
To summarize, every spectral diagnostic method implemented with linear excitation results in a very poor spatial resolution, a frequent need for multiple sources, a limited sensitivity, and an impossibility to get information at the cellular scale.